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Summary
This summary is machine-generated.

Artificial intelligence (AI) in infection biology evolved from simple automation to a versatile "Swiss army knife." This shift, accelerated by the COVID-19 pandemic, enables sophisticated analysis of host-pathogen interactions using diverse data types.

Keywords:
Artificial intelligenceComputer visionDeep learningHost–pathogen interactionsInfection biologyMachine learningNatural language processingPathogensProtein–protein interactionsVirology

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Area of Science:

  • Infection Biology
  • Computational Biology
  • Artificial Intelligence

Background:

  • AI applications in infection biology were limited to task automation (
  • sorting machine
  • paradigm) due to resistance to quantitative methods.
  • The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic catalyzed rapid AI advancements in the field.

Purpose of the Study:

  • To outline the evolution of AI in infection biology from basic automation to a versatile tool (
  • Swiss army knife
  • paradigm).
  • To illustrate AI applications across image, molecular, and language data for understanding host-pathogen interactions.
  • To demystify AI for infection biologists by explaining terminology and providing a practical guide.

Main Methods:

  • Review and synthesis of AI applications in infection biology.
  • Illustration of AI use cases across different data modalities (images, molecular data, language data).
  • Explanation of fundamental AI terminology and subfield relationships.
  • Inclusion of a practical guide for AI implementation (software installation, data preparation, model utilization).

Main Results:

  • AI in infection biology has matured beyond simple automation to address complex challenges.
  • Successful AI applications are demonstrated for analyzing diverse data types, aiding in host-pathogen interaction studies.
  • The transition to a versatile AI toolkit empowers infection biologists with advanced analytical capabilities.

Conclusions:

  • AI has become an indispensable and versatile tool in infection biology, transitioning from basic automation to sophisticated problem-solving.
  • The COVID-19 pandemic accelerated AI adoption and demonstrated its potential in tackling critical infectious disease challenges.
  • This work provides a foundational understanding and practical guidance for infection biologists to integrate AI into their research.